C S Ramakrishna Tejasvi supervised by Prof. Ponnurangam Kumaraguru received his Master of Science – Dual Degree  in Computational Linguistics (CLD). Here’s a summary of his research work on Personal Narratives in Online Political Discussions:

Engaging diverse participants in meaningful online political discussions remains a crucial challenge for contemporary democratic societies. Two central barriers to vibrant political discourse online are cross-partisan communication divides, where opposing ideological groups struggle to interact constructively, and the limited participation from politically disinclined individuals (PDIs), who often perceive themselves as lacking sufficient political knowledge or fear negative social consequences. Although existing literature presents mixed findings regarding the efficacy of personal narratives in political communication, this thesis investigates the potential of personal narratives—defined as short, first-person accounts emphasizing personal experiences—to bridge these divides and increase participation. Experimental research has shown that personal narratives can foster empathy, respect, and trust across ideological boundaries by enabling identification and emotional engagement. Conversely, some studies suggest that personal narratives in social media environments can inadvertently reinforce in-group solidarity, strengthen partisan identities, and amplify polarization due to platform-specific affordances, such as quantifiable feedback mechanisms. To resolve these discrepancies and comprehensively evaluate the role of personal narratives in real-world settings, this research conducts a large-scale computational analysis of political discussions on Reddit. Utilizing a BERT-based text classifier to identify personal narratives, alongside computational methods to infer user ideology and participation patterns, the analysis reveals encouraging results. First, politically disinclined individuals are significantly more likely to contribute personal narratives in political communities compared to their politically active counterparts, and such narratives notably increase their continued engagement over time. Additionally, personal narratives posted by PDIs consistently receive more positive feedback from community members relative to their non-narrative contributions, suggesting their unique value in enhancing inclusive discourse. Furthermore, when examining cross-partisan interactions, personal narratives exhibit varied impacts: notably, right-leaning individuals using personal narratives receive more favourable feedback from left-leaning communities, indicative of reduced partisan animosity and increased openness toward opposing viewpoints. However, this positive effect is asymmetrical, as similar outcomes are not consistently observed for left-leaning individuals. Additionally, while personal narratives alone do not substantially increase the probability of replies across ideological divides, they do significantly mitigate hostility levels, fostering a more respectful cross-partisan environment. This thesis argues that personal narratives not only empower politically disinclined individuals by lowering barriers to participation but also partially alleviate polarization by fostering empathy and respect in cross-partisan settings. These findings highlight personal narratives as valuable tools for enhancing democratic engagement. Future research could further explore the conditions under which personal narratives exert their strongest positive effects, as well as examine methods to systematically encourage the use of inclusive and empathetic storytelling within contentious political environments online.   

 May 2025